# A tibble: 274 × 2
org_code admissions
<fct> <dbl>
1 RF4 5060
2 R1H 6943
3 AD913 0
4 RYX 0
5 RQM 3597
6 RJ6 2202
7 Y02696 0
8 NX122 0
9 RVR 3360
10 RJ1 3181
11 Y03082 0
12 RQX 1684
13 RY9 0
14 RYJ 3270
15 RJZ 4477
16 RAX 1839
17 RJ2 4967
18 R1K 4659
19 RP6 11
20 RAT 0
21 RAP 2564
22 Y02973 0
23 AF003 0
24 AF002 0
25 RAL 3872
26 Y03047 0
27 RJ7 3814
28 F84747 0
29 RAS 2126
30 Y03094 0
31 E84068 0
32 RKE 1347
33 RRV 2182
34 Y02147 0
35 Y03201 0
36 NL7 0
37 8J094 0
38 RDD 2468
39 RC1 2022
40 M85813 0
41 RQ3 920
42 RJF 1870
43 RGT 3318
44 RFS 1996
45 NQ108 0
46 RDE 2597
47 Y03571 0
48 RTG 3745
49 RY8 0
50 NNJ 0
51 RWH 3222
52 NQ106 0
53 RLT 1119
54 NTPAL 0
55 NEH06 0
56 RR1 6006
57 RY4 0
58 RQQ 856
59 RGQ 1998
60 RGP 1242
61 RNQ 2555
62 C82038 0
63 RY5 18
64 NJS05 0
65 RC9 2650
66 C82009 0
67 NLO11 0
68 NLO09 0
69 RQ8 2291
70 RD8 1468
71 Y02652 0
72 RM1 2612
73 RGN 2406
74 RNS 3303
75 NMH01 0
76 NR3 0
77 RX1 4076
78 NLO10 0
79 C82010 0
80 NLO12 0
81 Y02428 0
82 RXK 3067
83 RK5 2765
84 RXW 2441
85 R1D 0
86 Y02615 0
87 RJC 1806
88 RAJ 2314
89 Y02470 0
90 Y02961 0
91 RNA 2425
92 RQW 1835
93 RCX 2049
94 RL4 2606
95 RWD 3502
96 RRK 2818
97 RKB 4077
98 RWE 3758
99 RJE 4511
100 RBK 1936
101 ATQ02 0
102 RWG 2701
103 RGR 2063
104 RWP 3201
105 RLQ 1185
106 REM 2718
107 RCF 1078
108 RBS 1130
109 RFF 2143
110 RXL 2247
111 RMC 2242
112 RAE 3045
113 NNF09 0
114 RY2 0
115 RWY 2628
116 RW3 3890
117 RLN 2650
118 RJR 1541
119 RXP 3387
120 RNN 0
121 RP5 3315
122 RJN 958
123 RXR 3054
124 NNF28 0
125 RR7 1670
126 RCD 988
127 RWA 3329
128 RV9 0
129 RXN 1721
130 Y01231 0
131 RR8 5213
132 Y02875 0
133 RY1 0
134 REP 111
135 Y01069 0
136 RBT 1840
137 RXF 5047
138 RNL 2055
139 RVW 1650
140 RTV 0
141 NLO01 0
142 RJL 2565
143 RTF 3975
144 RW6 5328
145 RT2 0
146 AC008 0
147 RQ6 2344
148 RM3 2637
149 AXT02 0
150 RCU 726
151 RHQ 2861
152 RTR 1919
153 RE9 1228
154 RVY 1905
155 RBN 3497
156 RWJ 2699
157 RMP 1708
158 RTD 2116
159 RFR 1671
160 RM2 2478
161 RTX 2019
162 RWW 2632
163 RY7 0
164 RBL 2546
165 AJN 0
166 RRF 1972
167 RCB 3543
168 RTK 1982
169 Y02688 0
170 NQT10 0
171 RWX 0
172 Y04538 0
173 RXH 3561
174 NLW 0
175 RXQ 2891
176 Y00058 0
177 NLT02 0
178 RJ8 1
179 RN7 2514
180 RBD 1310
181 RVV 3336
182 RXC 2801
183 DD401 0
184 RDU 6054
185 R1J 0
186 RTE 3464
187 RN3 2065
188 RN5 2428
189 NDA57 0
190 R1F 744
191 RYY 0
192 NR5 0
193 RWF 3677
194 RPA 2263
195 RVJ 2324
196 RBZ 1117
197 L83087 0
198 RNU 0
199 RTH 3100
200 NLX02 0
201 RK9 3008
202 RD3 1692
203 RHU 2921
204 RPC 31
205 RHW 3063
206 REF 2489
207 RH8 1849
208 RA2 2017
209 RD1 2103
210 RNZ 1062
211 Y02666 0
212 RH5 0
213 RYF 0
214 NTP11 0
215 RW1 9
216 NTPAD 0
217 RTP 2264
218 RDR 0
219 RBA 1773
220 AAH 0
221 RDZ 1876
222 RA9 2530
223 RHM 3456
224 RA7 2918
225 RYR 3199
226 RA3 1007
227 NDA56 0
228 G82071 0
229 NDA55 0
230 NLX24 0
231 RA4 1404
232 NAX 0
233 R1A 0
234 Y02646 0
235 NTP08 0
236 Y02613 0
237 RDY 3
238 Y02662 0
239 Y02568 0
240 Y02585 0
241 RYW 0
242 NLO20 0
243 Y02987 0
244 Y02596 0
245 NLO02 0
246 Y02565 0
247 E84069 0
248 Y02692 0
249 Y03218 0
250 Y03007 0
251 C83023 0
252 NNF70 0
253 NNF94 0
254 NNF99 0
255 R0A 6874
256 Y02532 0
257 Y03645 0
258 Y02572 0
259 Y02533 0
260 NQT5F 0
261 NNF76 0
262 NNF18 0
263 NTV0B 0
264 Y02676 0
265 Y00751 0
266 Y02816 0
267 NDJ 0
268 Y03051 0
269 NQT5H 0
270 Y02584 0
271 NTV0W 0
272 NNFA7 0
273 RW4 0
274 AXG 0From One Report, Many
Using Parameterized Reporting to Generate
Dozens, Hundreds, or Thousands of Reports
at the Same Time
David Keyes // R for the Rest of Us
About Me
Why Parameterized Reporting?
Making multiple reports is tedious
Making multiple reports is error-prone
Making multiple reports is often not feasible
Parameterized Reporting Changes Everything
Or Imagine Having to Make One Report for Each NHS Trust in England
Parameterized Reporting is the Solution
How Parameterized Reporting Works
Make a Report
---
title: "Total Admissions Over Time"
format:
html:
embed-resources: true
css: styles.css
execute:
echo: false
warning: false
message: false
editor_options:
chunk_output_type: console
---
```{r}
library(tidyverse)
library(NHSRdatasets)
library(scales)
```
This chart shows total admissions over time in all NHS trusts.
```{r}
ae_attendances %>%
summarize(total_admissions = sum(admissions),
.by = period) %>%
ggplot(aes(x = period,
y = total_admissions)) +
geom_line(alpha = 0.9,
color = "#005EB8") +
geom_area(alpha = 0.5,
fill = "#005EB8") +
scale_y_continuous(labels = comma_format()) +
theme_minimal(base_family = "Frutiger") +
theme(plot.title = element_text(face = "bold"),
plot.title.position = "plot",
panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank())
```Manually Render One Report
Make a Report for One Location
---
title: "Total Admissions Over Time"
format:
html:
embed-resources: true
css: styles.css
execute:
echo: false
warning: false
message: false
editor_options:
chunk_output_type: console
---
```{r}
library(tidyverse)
library(NHSRdatasets)
library(scales)
```
This chart shows total admissions over time at RF4.
```{r}
ae_attendances %>%
filter(org_code == "RF4") %>%
summarize(total_admissions = sum(admissions),
.by = period) %>%
ggplot(aes(x = period,
y = total_admissions)) +
geom_line(alpha = 0.9,
color = "#005EB8") +
geom_area(alpha = 0.5,
fill = "#005EB8") +
scale_y_continuous(labels = comma_format()) +
theme_minimal(base_family = "Frutiger") +
theme(plot.title = element_text(face = "bold"),
plot.title.position = "plot",
panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank())
```Add a Parameter to Our Report
---
title: "Total Admissions Over Time"
format:
html:
embed-resources: true
css: styles.css
execute:
echo: false
warning: false
message: false
editor_options:
chunk_output_type: console
params:
location: "RF4"
---
```{r}
library(tidyverse)
library(NHSRdatasets)
library(scales)
```
This chart shows total admissions over time at `r params$location`.
```{r}
ae_attendances %>%
filter(org_code == params$location) %>%
summarize(total_admissions = sum(admissions),
.by = period) %>%
ggplot(aes(x = period,
y = total_admissions)) +
geom_line(alpha = 0.9,
color = "#005EB8") +
geom_area(alpha = 0.5,
fill = "#005EB8") +
scale_y_continuous(labels = comma_format()) +
theme_minimal(base_family = "Frutiger") +
theme(plot.title = element_text(face = "bold"),
plot.title.position = "plot",
panel.grid.minor = element_blank(),
panel.grid.major.x = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank())
```Manually Render the Report (Again)
Manually Render Multiple Reports
Semi-Manually Render Report with R Script File
Automatically Render Multiple Reports with R Script File
# Load packages
library(tidyverse)
library(NHSRdatasets)
library(quarto)
# Create a vector of all locations
locations <- ae_attendances %>%
distinct(org_code) %>%
mutate(org_code = as.character(org_code)) %>%
pull(org_code)
# Create a tibble with information on the:
# input R Markdown document
# output HTML file
# parameters needed to knit the document
reports <- tibble(
input = "report.qmd",
output_file = str_glue("{locations}.html"),
execute_params = map(locations, ~list(location = .))
)
# Use the tibble to generate all of our reports
pwalk(reports, quarto_render)Summary
- Create report
- Add parameter to report
- Create render.R script file
- Create vector of all locations
- Create tibble with information about all reports
- Use reports tibble to render all reports
Learn More
Don’t Do It By Hand, Use Parameterized Reporting
Less tedious
Less error-prone
Makes it possible to generate reports that would not otherwise be feasible
Questions?
Ask in the chat or by email: david@rfortherestofus.com